Every Friday on Statistics Views, we publish layman's abstracts of new articles from our prestigious portfolio of journals in statistics. The aim is to highlight the latest research to a broader audience in an accessible format. This article featured today is from Statistics in Medicine: Meta-analysis of aggregate data on medical events by Björn Holzhauer.
Read the layman's abstract below.
Björn Holzhauer. (2017), Meta-analysis of aggregate data on medical events, Statistics in Medicine, 36, pages...

Collaboration is one of those words that means many things to different people, ranging from work between two individuals to vast efforts involving many people across multiple organizations. The American Statistical Association (ASA) wants to encourage and recognize outstanding collaborations.

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2018-02-14T10:00:00ZWell‐posedness, blow‐up phenomena and analyticity for a two‐component higher order Camassa–Holm systemhttp://www.statisticsviews.com/details/journalArticle/10863322/Wellposedness-blowup-phenomena-and-analyticity-for-a-twocomponent-higher-order-C.html

Abstract
In this paper, the local well‐posedness for the Cauchy problem of a two‐component higher‐order Camassa–Holm system (2HOCH)
is established in Besov spaces
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r
s
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...

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2018-02-14T00:55:47ZBenefits of spatiotemporal modeling for short‐term wind power forecasting at both individual and aggregated levelshttp://www.statisticsviews.com/details/journalArticle/10863336/Benefits-of-spatiotemporal-modeling-for-shortterm-wind-power-forecasting-at-both.html

The share of wind energy in total installed power capacity has grown rapidly in recent years. Producing accurate and reliable
forecasts of wind power production, together with a quantification of the uncertainty, is essential to optimally integrate
wind energy into power systems. We build spatiotemporal models for wind power generation and obtain full probabilistic forecasts
from 15 min to 5 h ahead. Detailed analyses of...

The National Institute for Statistical Sciences (NISS) are calling for nominations for the 2018 National Institute of Statistical Sciences’ (NISS) Jerome Sacks Award for Outstanding Cross-Disciplinary Research.
The award was set up in 2000 and named after the founding director of the National Institute of Statistical Sciences. It recognises ‘sustained, high quality cross-disciplinary research involving the statistical sciences’.

Towards the end of last year, Wiley was proud to publish Advanced Analysis of Variance, which introduces a revolutionary new model for the statistical analysis of experimental data
In this important book, internationally acclaimed statistician, Chihiro Hirotsu, goes beyond classical analysis of variance (ANOVA) model to offer a unified theory and advanced techniques for the statistical analysis of experimental data. Dr. Hirotsu introduces the groundbreaking concept of advanced analysis of variance...

Abstract
This work does a systematic comparative evaluation of 2 methods originating from different fields, both dedicated to the problem
of curve resolution/unmixing: multivariate curve resolution–alternating least squares (MCR‐ALS) and band‐target entropy minimization
(BTEM). The MCR‐ALS factorizes the data matrix into spectral and concentration profiles that satisfy constraints expressing
physicochemical knowledge on the analyzed...

The binomial model is a standard framework used to introduce risk neutral pricing of financial assets. Martingale representation,
backward stochastic differential equations, and the Malliavin calculus are difficult concepts in a continuous‐time setting.
This paper presents these ideas in the simple, discrete‐time binomial model.

A novel method for offline detection of multiple change points in multidimensional time series is proposed. It is based on
the notion of ε‐complexity of continuous vector functions. The proposed methodology does not use any prior information on data‐generating
mechanisms; therefore, it can be applied to multidimensional time series of arbitrary nature. Its performance is demonstrated
in simulations and an application to...